Allen School researchers are at the forefront of exciting developments in AI spanning machine learning, computer vision, natural language processing, robotics and more.
We cultivate a deeper understanding of the science and potential impact of rapidly evolving technologies, such as large language models and generative AI, while developing practical tools for their ethical and responsible application in a variety of domains — from biomedical research and disaster response, to autonomous vehicles and urban planning.
Groups & Labs
SAMPL
SAMPL is an interdisciplinary machine learning research group exploring problems across the system stack, including deep learning frameworks, specialized hardware for training and inference, new intermediate representations and more.
Bespoke Silicon Group
The Bespoke Silicon Group aims to bring hardware design to its highest art and rapidly conceive of, design and implement entirely new kinds of hardware faster than has ever been done before.
Allen School Faculty
Assistant Professor
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Associate Professor
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Centers & Initiatives
Globe.AI is a multidisciplinary community of researchers at the University of Washington who aim to create equitable, responsive AI technologies that can adapt to individuals from diverse cultures and communities, including to different norms, languages, behaviors, and communication styles.
MEM-C is a NSF Materials Research Science and Engineering Center that integrates materials innovations with theory and computation to advance spin-photonic nanostructures and elastic layered quantum materials, aided by an “AI Core” that integrates artificial intelligence-driven materials discovery.
Highlights
Allen School News
Professor Magda Balazinska was honored for her influential contributions in data management and data science, while Professor Shwetak Patel was recognized for his groundbreaking work applying computing to health and sustainability.
Forbes
Kim was honored in the health care and sciences category for his work with professor Su-In Lee in the Allen School’s AI for bioMedical Sciences (AIMS) Lab on methods for improving the transparency, safety and explainability of medical AI systems.
Allen School News
In December, Feng was named among the 2026 class of NVIDIA Graduate Fellows in recognition of his work on model collaboration, where “multiple AI models, trained on different data, by different people, and thus possess diverse skills and strengths, collaborate, compose and complement each other.”